1) Pandas

Pandas is one of the most popular data analysis and data manipulation libraries. It is an open-source library. DataFrame is the chief data structure of the Pandas library. DataFrame stores and manages the data in the table. It can be done by manipulating rows and columns. It allows dataset joining, merging and reshaping.
Hence, when millions of petabytes of data are to be analyzed, Pandas is much helpful in this case. Using Pandas, Data can be easily and effectively analyzed.

2) NumPy

Numerical Python, in short, NumPy, is an open-source library. It is an incredible Python library for scientific calculations. It also allows for accomplishing matrix operations. NumPy is used to perform operations on the array. As it works on an array, it permits us to reorganize a large set of data.

3) Spacy

Till now, Pandas and NumPy taught us to clean and manipulate data. Spacy manipulates free data into structured data. It is used as an NLP (Natural Language Processing) library. Many human languages are also supported by this library.

4) SciPy

It is an open-source library which is based on the concept of NumPy which provides many effective numerical routines. It can perform integration and linear algebra and has high-level features for data manipulating and visualizing. It is a key library for data processing.